Title: Extracting semantic relations to enrich domain ontologies
Authors: Shen, Minxin
Liu, Duen-Ren
Huang, Yu-Siang
資訊管理與財務金融系 註:原資管所+財金所
Department of Information Management and Finance
Keywords: Ontology learning;Relation extraction;Semantic relation;Text mining
Issue Date: 1-Dec-2012
Abstract: Domain ontologies facilitate the organization, sharing and reuse of domain knowledge, and enable various vertical domain applications to operate successfully. Most methods for automatically constructing ontologies focus on taxonomic relations, such as is-kind-of and is-part-of relations. However, much of the domain-specific semantics is ignored. This work proposes a semi-unsupervised approach for extracting semantic relations from domain-specific text documents. The approach effectively utilizes text mining and existing taxonomic relations in domain ontologies to discover candidate keywords that can represent semantic relations. A preliminary experiment on the natural science domain (Taiwan K9 education) indicates that the proposed method yields valuable recommendations. This work enriches domain ontologies by adding distilled semantics.
URI: http://dx.doi.org/10.1007/s10844-012-0210-y
http://hdl.handle.net/11536/20605
ISSN: 0925-9902
DOI: 10.1007/s10844-012-0210-y
Journal: JOURNAL OF INTELLIGENT INFORMATION SYSTEMS
Volume: 39
Issue: 3
Begin Page: 749
End Page: 761
Appears in Collections:Articles


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